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CS&SE - CITS4243 Advanced Databases

 
CITS4243 Advanced Databases
Laboratory Sheet 2

CITS4243 Advanced Databases - Lab Sheet 2


Weka (Waikato Environment for Knowledge Analysis) is an open source suite of machine learning software developed at University of Waikato, New Zealand.Weka is written in Java and hence platform-independent. We will use Weka for experimenting with some machine learning and clustering algorithms.

You can download Weka from the Weka home page:
http://www.cs.waikato.ac.nz/ml/weka/

I have downloaded two versions of Weka:





Note that, both of these are Windows executables. You can download the linux or Mac OS X executables from the Weka home page. You can also download the Weka manual from the Weka home page. However, I have downloaded a copy here:



Weka can be used both from command line and through a GUI. We will be using Weka mostly through a GUI. It is very easy to use Weka through a GUI and you can start using Weka after a quick read through some part of the manual. We will mainly use the Weka neural network simulator and clustering tools. The neural network simulator is called "MultilayerPerceptron" in Weka. Here is an additional tutorial that will help you to quickly learn how to use Weka:



Weka uses a special data file format and all Weka data files must have an .arff extension. There is a link in the left panel of the Weka home page called "Datasets" that points to several example datasets.

is an example dataset. It is a jar file and you can extract individual data files using Winzip or Winrar programs.


Your task is to familiarize yourself with the Weka system. We will mainly use the "Explorer" part of Weka (You are given the "explorer" as one of four options when you launch Weka). The second project will be announced within a few days.

I will post some additional materials on Weka in the coming days.


Amitava Datta
May 2011


School of Computer Science & Software Engineering
The University of Western Australia
Crawley, Western Australia, 6009.
Phone: +61 8 9380 2716 - Fax: +61 8 9380 1089.
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